Project description:Natural flavonoid pectolinarigenin (PEC) was reported to alleviate tubulointerstitial fibrosis of unilateral ureteral obstruction (UUO) mice in our previous study. To further investigate nephroprotective effects of PEC in hyperuricemic nephropathy (HN), adenine and potassium oxonate induced HN mice and uric acid-treated mouse kidney epithelial (TCMK-1) cells were employed in the study. As a result, PEC significantly lowered serum uric acid level and restored hyperuricemia-related kidney injury in HN mice. Meanwhile, PEC alleviated inflammation, fibrosis and reduced adipokine FABP4 content in the kidneys of HN mice and uric acid-treated TCMK-1 cells. Mechanistically, PEC inhibited the TGF-β1 expression as well as the phosphorylation of transcription factor SMAD3 and STAT3 to regulate the corresponding inflammatory and fibrotic gene expression in kidney tissues. In conclusion, our results suggested that PEC could inhibit the activation of SMAD3 and STAT3 signaling to suppress inflammation and fibrosis, thereby alleviate HN in mice.
Project description:Background and Objective: Hypertensive nephropathy (HN) requires a kidney biopsy as gold-standard for its diagnosis but histological findings are not entirely specific and lack specific prognostic markers. We aimed at defining prognostic candidate markers based on glomerular protein signatures. Method: We included adult patients (n=17) with an eGFR >30 ml/min/1.73m2 and proteinuria <3g/d from the Norwegian Kidney Biopsy Registry: stable patients (n=9) and subjects with HN progression (n=8) leading to end-stage renal disease (ESRD) within 20 years of follow-up. Glomerular cross-sections were microdissected from archival kidney biopsy sections and processed for protein extraction. Proteomic analyses were performed using Q-exactive HF mass spectrometer and relative glomerular protein abundance were compared between progressive vs non-progressive patients. Results: Amongst 1870 quality filtered proteins, we identified 58 proteins with an absolute fold change (FC)>1.5, p<0.05, including 17 proteins with absolute FC >2, indicative of HN progression (highest FC: Cadherin 16 and UDP-glucuronosyl-transferase 2B7). Hierarchical cluster and principal component analysis (PCA) with the 17 proteins showed clear separation of samples into HN progressors and non-progressors. Supervised classifier analysis (K nearest neighbour) identified a set of five proteins which classified 16/17 samples correctly. Applying Geneset Enrichment Analysis (GSEA), in general metabolic pathways were enriched in progressors, and structural cell pathways enriched in non-progressors. Pathway analysis identified Epithelial Adherens Junction Signaling as the most affected canonical pathway. The signature of HN progression is different from the respective signature of IgA progression. Conclusion: Glomerular proteomic profiling can be used to discriminate progressors from non-progressors in HN.
Project description:We comparatively evaluated transcriptomes from renal biopsies obtained from patients with T2DN or HN, main causes of CKD, and control renal tissues (n=6 per group). RNA was extracted from formalin-fixed and paraffin-embedded kidney samples and processed for RNA sequencing. Principal component analysis effectively separated diseased and control tissues. Gene and protein expression profiles revealed that EMT-related markers were upregulated in both diseases. Moreover, activation of CD4 and CD lymphocytes, as well as upregulation of the complement system were also observed in both T2DN and HN. These data, suggesting partially common pathogenetic mechanisms, were largely confirmed by IHC analysis.
Project description:Hypertensive nephropathy (HN) is a leading cause of chronic kidney disease (CKD), but molecular mechanisms underlying disease progression remain poorly understood. We aimed to identify transcriptomic signatures associated with disease progression and to localize these signatures within renal architectures. Patients with biopsy-proven HN were selected from the Norwegian Kidney Biopsy Registry and stratified after ≥5 years of follow-up into early stable (ES), early progressor (EP), late stable (LS) and late progressor (LP) based on baseline kidney function and annual eGFR decline. Bulk transcriptomic profiling was performed in a discovery cohort and validated in an independent cohort using nCounter profiling. Spatial transcriptomics was applied to map progression-associated signatures to nephron compartments. Bulk RNA sequencing identified 415 differentially expressed genes (DEGs) between ES and EP, and 692 between LS and LP samples. ES was enriched in circadian rhythm pathways, with reduced NR1D1 and NR1D2 expression in EP. LP was associated with metabolic reprogramming including glutathione, retinol and amino acid metabolism. Random forest modelling identified NR1D1 gene expression as a key classifier, validated in an independent cohort. Spatial transcriptomics revealed nephron segment-specific expression patterns, including a proximal tubule cluster enriched in ferroptosis in LP. Comparative nephron-segment analyses across groups revealed progression-associated biomarkers, including CHGA, CCN2 and SFRP2 in glomeruli, and APOE in proximal tubules. HN progression appears to involve stage-specific and compartmentalized molecular programs. Integration of bulk and spatial transcriptomics identifies candidate biomarkers and pathways, potentially supporting innovative prognostic stratification and therapeutic strategies.
Project description:Hypertensive nephropathy (HN) is a leading cause of chronic kidney disease (CKD), but molecular mechanisms underlying disease progression remain poorly understood. We aimed to identify transcriptomic signatures associated with disease progression and to localize these signatures within renal architectures. Patients with biopsy-proven HN were selected from the Norwegian Kidney Biopsy Registry and stratified after ≥5 years of follow-up into early stable (ES), early progressor (EP), late stable (LS) and late progressor (LP) based on baseline kidney function and annual eGFR decline. Bulk transcriptomic profiling was performed in a discovery cohort and validated in an independent cohort using nCounter profiling. Spatial transcriptomics was applied to map progression-associated signatures to nephron compartments. Bulk RNA sequencing identified 415 differentially expressed genes (DEGs) between ES and EP, and 692 between LS and LP samples. ES was enriched in circadian rhythm pathways, with reduced NR1D1 and NR1D2 expression in EP. LP was associated with metabolic reprogramming including glutathione, retinol and amino acid metabolism. Random forest modelling identified NR1D1 gene expression as a key classifier, validated in an independent cohort. Spatial transcriptomics revealed nephron segment-specific expression patterns, including a proximal tubule cluster enriched in ferroptosis in LP. Comparative nephron-segment analyses across groups revealed progression-associated biomarkers, including CHGA, CCN2 and SFRP2 in glomeruli, and APOE in proximal tubules. HN progression appears to involve stage-specific and compartmentalized molecular programs. Integration of bulk and spatial transcriptomics identifies candidate biomarkers and pathways, potentially supporting innovative prognostic stratification and therapeutic strategies.
Project description:Hypertensive nephropathy (HN) is a leading cause of chronic kidney disease (CKD), but molecular mechanisms underlying disease progression remain poorly understood. We aimed to identify transcriptomic signatures associated with disease progression and to localize these signatures within renal architectures. Patients with biopsy-proven HN were selected from the Norwegian Kidney Biopsy Registry and stratified after ≥5 years of follow-up into early stable (ES), early progressor (EP), late stable (LS) and late progressor (LP) based on baseline kidney function and annual eGFR decline. Bulk transcriptomic profiling was performed in a discovery cohort and validated in an independent cohort using nCounter profiling. Spatial transcriptomics was applied to map progression-associated signatures to nephron compartments. Bulk RNA sequencing identified 415 differentially expressed genes (DEGs) between ES and EP, and 692 between LS and LP samples. ES was enriched in circadian rhythm pathways, with reduced NR1D1 and NR1D2 expression in EP. LP was associated with metabolic reprogramming including glutathione, retinol and amino acid metabolism. Random forest modelling identified NR1D1 gene expression as a key classifier, validated in an independent cohort. Spatial transcriptomics revealed nephron segment-specific expression patterns, including a proximal tubule cluster enriched in ferroptosis in LP. Comparative nephron-segment analyses across groups revealed progression-associated biomarkers, including CHGA, CCN2 and SFRP2 in glomeruli, and APOE in proximal tubules. HN progression appears to involve stage-specific and compartmentalized molecular programs. Integration of bulk and spatial transcriptomics identifies candidate biomarkers and pathways, potentially supporting innovative prognostic stratification and therapeutic strategies.
Project description:Proliferative breast lesions, such as simple ductal hyperplasia (SH) and atypical ductal hyperplasia (ADH), are candidate precursors to ductal carcinoma in situ (DCIS) and invasive cancer. To better understand their relationship to more advanced disease, we used microdissection and DNA microarrays to profile the gene expression of patient-matched histologically normal (HN), ADH, and DCIS from 12 patients with ER+ sporadic breast cancer. SH were profiled from a subset of cases. We found 837 differentially expressed genes between DCIS-HN and 447 between ADH-HN, with >90% of the ADH-HN genes also present among the DCIS-HN genes. Only 61 genes were identified between ADH-DCIS. Expression differences were reproduced in an independent cohort of patient-matched lesions by qRT-PCR. Many breast cancer-related genes and pathways were dysregulated in ADH and maintained in DCIS. Particularly, cell adhesion and extracellular matrix (ECM) interactions were overrepresented. Focal adhesion was the top pathway in each gene set. We conclude that ADH and DCIS share highly similar gene expression and are distinct from HN. In contrast, SH appear more similar to HN. These data provide genetic evidence that ADH (but not SH) are often precursors to cancer and suggest cancer-related genetic changes, particularly adhesion and ECM pathways, are dysregulated prior to invasion and even before malignancy is apparent. These findings could lead to novel risk stratification, prevention, and treatment approaches. Patient-matched (HN, SH, ADH, DCIS) samples were isolated from within patients with ER+ sporadic breast cancers via laser capture microdissection. Use of patient-matched samples decreases between patient variations.
Project description:Rice productivity relies heavily on nitrogen fertilization, and improving nitrogen use efficiency (NUE) is important for hybrid rice breeding. Reducing nitrogen inputs is the key to achieving sustainable rice production and reducing environmental problems. Here, we analyzed the genome-wide transcriptomic changes in microRNAs (miRNAs) in the indica rice restorer cultivar NH511 (Nanhui 511) under high (HN) and low nitrogen (LN) conditions. The results showed that NH511 is sensitive to nitrogen supplies and HN conditions promoted the growth its lateral roots at the seedling stage. Furthermore, we identified 483 known miRNAs and 128 novel miRNAs by small RNA sequencing in response to nitrogen in NH511. We also detected 100 differentially expressed genes (DEGs), including 75 upregulated and 25 downregulated DEGs, under HN conditions. Among these DEGs, 43 miRNAs that exhibited a 2-fold change in their expression were identified in response to HN conditions, including 28 upregulated and 15 downregulated genes. Additionally, some differentially expressed miRNAs were further validated by qPCR analysis, which showed that miR443, miR1861b, and miR166k-3p were upregulated, whereas miR395v and miR444b.1 were downregulated under HN conditions. Moreover, the degradomes of possible target genes for miR166k-3p and miR444b.1 and expression variations were analyzed by qPCR at different time points under HN conditions. Our findings revealed comprehensive expression profiles of miRNAs responsive to HN treatments in an indica rice restorer cultivar, which advances our understanding of the regulation of nitrogen signaling mediated by miRNAs and provides novel data for high-NUE hybrid rice cultivation.
Project description:Gene expression in histologically normal epithelium from breast cancer patients and cancer-free prophylactic mastectomy patients share a similar profile Introduction: We hypothesized that gene expression in histologically normal epithelium (NlEpi) would differ in breast cancer patients (HN) compared to usual-risk controls undergoing reduction mammoplasty (RM), and that gene expression in NlEpi from cancer-free prophylactic mastectomies from high-risk women (PM), would resemble HN gene expression. Methods: We analyzed gene expression in 73 NlEpi samples microdissected from frozen tissue. In 42 cases, we used Affymetrix HU133A microarrays to compare gene expression in 18 RM vs 18 age-matched HN (9 ER+, 9 ER-) and 6 PM. Data were validated with qPCR in 31 independent NlEpi samples (8 RM, 17 HN, 6 PM). Results: 98 probesets (86 genes) were differentially expressed between RM and HN samples. Perfoming supervised hierarchical analysis with these 98 probesets, PM and HN samples clustered together, away from RM samples. qPCR validation of independent samples was high (84%) and uniform in RM vs HN, and lower (58%), but more heterogeneous, in RM vs PM. The 86 genes were implicated in many processes including transcription and the MAPK pathway. Conclusion: Gene expression differs between NlEpi of cancer cases and controls. The cancer cases' profile can be discerned in high-risk NlEpi. This suggests that the profile is not an effect of the tumor, but may mark increased risk and reveal breast cancer's earliest genomic changes. We determined that 98 probesets significantly differed between reduction mammoplasty and histologically normal epithelium from breast cancer patients. We also found that the histologically normal epithelium from prophylactic mastectomy patients' gene expression was more similar to histologically normal epithelium from breast cancer patients' than to reduction mammoplasty patients' gene expression. These results demonstrate that gene expression differs between NlEpi of cancer cases and controls. The cancer cases’ profile can be discerned in high-risk NlEpi. This suggests that the profile is not an effect of the tumor, but may mark increased risk and reveal breast cancer's earliest genomic changes.
Project description:Proliferative breast lesions, such as simple ductal hyperplasia (SH) and atypical ductal hyperplasia (ADH), are candidate precursors to ductal carcinoma in situ (DCIS) and invasive cancer. To better understand their relationship to more advanced disease, we used microdissection and DNA microarrays to profile the gene expression of patient-matched histologically normal (HN), ADH, and DCIS from 12 patients with ER+ sporadic breast cancer. SH were profiled from a subset of cases. We found 837 differentially expressed genes between DCIS-HN and 447 between ADH-HN, with >90% of the ADH-HN genes also present among the DCIS-HN genes. Only 61 genes were identified between ADH-DCIS. Expression differences were reproduced in an independent cohort of patient-matched lesions by qRT-PCR. Many breast cancer-related genes and pathways were dysregulated in ADH and maintained in DCIS. Particularly, cell adhesion and extracellular matrix (ECM) interactions were overrepresented. Focal adhesion was the top pathway in each gene set. We conclude that ADH and DCIS share highly similar gene expression and are distinct from HN. In contrast, SH appear more similar to HN. These data provide genetic evidence that ADH (but not SH) are often precursors to cancer and suggest cancer-related genetic changes, particularly adhesion and ECM pathways, are dysregulated prior to invasion and even before malignancy is apparent. These findings could lead to novel risk stratification, prevention, and treatment approaches. Patient-matched (HN, SH, ADH, DCIS) samples were isolated from within patients with ER+ sporadic breast cancers via laser capture microdissection. Use of patient-matched samples decreases between patient variations. Forty total samples were analyzed via Affymetrix U133A. Patient age ranged from 48-92. Case numbers correspond to individual patients. Each sample is identified by case number, histologic lesion and corresponding microarray ID.